Urban logistics is under pressure. Cities want fewer vehicles, lower emissions, and less congestion, while home delivery demand continues to grow. The Picnic case shows that these goals are not mutually exclusive when data, operations, and vehicle technology are tightly integrated.
Picnic operates one of Europe’s largest fully electric last-mile fleets, with around 4,500 custom-built delivery vehicles in the Netherlands, Germany, and France. As an online supermarket, Picnic works with strict twenty-minute delivery time slots and highly optimised routes. In such a model, every kilometre and every kilowatt matters. As the company scaled up internationally and its fleet aged, simple rules of thumb were no longer sufficient. The central question became: how do you maximise vehicle utilisation without adding more vehicles to already crowded cities?
From static planning to real-time decision-making
The key step was shifting from static assumptions to real-time insight. Picnic developed its own Vehicle-to-Trip system that matches vehicles to routes in real time on each shift. Instead of assuming a fixed range per vehicle, the system looks at the actual state of charge, energy consumption profiles, payload, route characteristics, and GPS data. This allows planners to answer very concrete operational questions: can this vehicle still do another trip today, and if so, which one?
The lesson for city logistics is clear. Electric fleets cannot be managed like diesel fleets. Battery performance varies by vehicle, day, and route. Only with real-time data can operators safely push utilisation without risking service failures.
Fewer vehicles, same (or more) work
The impact is significant. Thanks to real-time visibility and smarter planning, Picnic reduced the size of its electric fleet in the Netherlands by 5-13 percent. That translates directly into fewer vehicles on the street, lower capital costs, and less pressure on charging infrastructure. Importantly, fewer vehicles did not mean fewer deliveries. Picnic can now handle more orders with the same—or even a smaller—fleet.
The benefits extend beyond daily operations. Picnic uses the data for longer-term fleet strategy, such as redistributing vehicles between hubs to balance mileage, planning maintenance based on actual use rather than fixed intervals, and monitoring battery health to detect ageing early. This extends vehicle lifetimes and improves the total cost of ownership.
Why this matters for cities
For cities struggling with congestion, zero-emission zones, and scarce curb space, this case challenges a common assumption: that growth in urban logistics inevitably means more vehicles. The Picnic example shows that operational intelligence can decouple demand growth from vehicle growth.
It also highlights an important governance lesson. Policies that simply restrict vehicle numbers or access risk missing out on efficiency gains within logistics operations. Cities benefit most when they set clear environmental and spatial goals, while leaving room for operators to innovate with data, algorithms, and fleet management.
A broader takeaway
The Picnic case underlines a broader trend in city logistics: the next efficiency gains will not come primarily from new vehicles, but from better use of existing ones. Real-time data, smart algorithms, and integrated fleet management are becoming as important as infrastructure and regulation. For cities aiming to reduce traffic while accommodating urban logistics, that shift is essential.
Source: Moove